MCP Fathom Server
Server Quality Checklist
Latest release: v1.0.0
- Disambiguation5/5
list_meetings and search_meetings have clearly distinct purposes: one filters and lists meetings, the other performs keyword search. No ambiguity.
Naming Consistency5/5Both tools use consistent verb_noun pattern: list_meetings and search_meetings. Naming is predictable and clear.
Tool Count4/5With only 2 tools, the server is minimal but appears focused on read operations for meeting data. The count is slightly low but appropriate for its narrow scope.
Completeness4/5The set covers listing and searching meetings, which covers common read operations. However, there is no tool to retrieve a specific meeting by ID, a minor gap.
Average 3.5/5 across 2 of 2 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
This repository is licensed under MIT License.
This repository includes a README.md file.
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How is the quality score calculated?
The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).
Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.
Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).
Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.
Tool Scores
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must convey behavior. It implies a read-only listing operation but does not explicitly state it is non-destructive, require authentication, or any rate limits. The return fields are mentioned, providing some transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise at two sentences, front-loading the action and return information. There is no fluff, and it is easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 9 optional parameters and no output schema, the description covers the basic purpose and return values but does not explain filter usage or output structure. It is adequate but not thorough.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description only generically mentions 'optional filters' without adding any meaning to individual parameters beyond what the schema already provides. No extra context is given.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it lists Fathom meetings with optional filters and specifies the return fields (titles, summaries, dates, participants). However, it does not differentiate from the sibling tool 'search_meetings', leaving ambiguity about when to use each.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'search_meetings'. It also does not mention any prerequisites, limitations, or context for filters.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must cover behavioral traits. It discloses the 30-day limit and disabled transcript search, but does not mention authentication needs, rate limits, pagination, or result ordering. The performance warning is useful but insufficient for full transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, each earning its place: first states purpose and fields, second adds critical usage constraints. No redundant or vague language. Front-loaded with the core action.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool lacks an output schema, yet the description does not mention what the search returns (e.g., a list of meeting objects, limited fields). It also does not specify the maximum number of results or sort order. Given the low complexity (2 params) and absence of output schema, the description should provide more details about the response format to be complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline is 3. The description adds context by mentioning the search fields (titles, summaries, action items) and the performance note about transcript search, which aligns with the schema descriptions. No additional syntax or usage details are provided beyond what the schema already states.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Search' and the resource 'meetings', specifying the fields (titles, summaries, action items) and the 30-day time constraint. It implicitly distinguishes from sibling tool 'list_meetings' which likely returns all meetings without keyword filtering.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit context: searches only last 30 days and transcript search is disabled by default for performance. While it doesn't explicitly state when not to use or name alternatives, the context is clear enough for an agent to decide against using it for older meetings or when transcript search is needed.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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